Business intelligence within commercial real estate: An application of the Motivation and Acceptance Model

by Janke, Scott M., Ph.D., CAPELLA UNIVERSITY, 2009, 112 pages; 3354948


The focus of this study was to identify the factors which determine the level of user acceptance of Business Intelligence (BI) in commercial real estate companies. The Technology Acceptance Model or TAM (Davis, 1989) is a well-researched theory of determining an end-user's intentions to use technology. This model posits that understanding a user's perceived usefulness of the technology and the user's perceived ease of use of the technology ultimately derives the user's theoretical intention to use the technology. While the TAM has been leveraged in many research studies, it has been viewed as lacking a complete picture of the end-user's true intention to use a new system. Many modified versions of the TAM have been developed to address additional aspects of human behavior that might determine a user's intention to use. One such model is the Motivation and Acceptance Model or MAM developed by Daniel Siegel (2008). MAM was previously tested on faculty at a college within a large Southwestern university on the faculty's acceptance of a new technology called LiveText. While the new MAM framework has only been tested within the confines of this one setting, the findings did show a strong correlation between faculty's perceptions and motivation to use LiveText and their subsequent use of LiveText. Leveraging this earlier work, the new MAM is utilized in the current study. This study is significant to the body of knowledge for two specific reasons. The first is the lack of empirical research on how the commercial real estate industry accepts and utilizes key developments in information technology, specifically BI. The second reason is to extend the development and testing of a new user acceptance model in different settings and applied to different technologies.

AdviserStephanie Fraser-Beekman
Source TypeDissertation
SubjectsManagement; Information science; Computer science
Publication Number3354948

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